Over the past two decades, the contact center industry has promised capabilities that will significantly improve customer experience. This is important because CX is now the top brand differentiator, with many consumers switching loyalties because of a single bad experience. Though it’s true that the contact center providers have delivered new capabilities such as omnichannel communications, self-service tools and more, consumer satisfaction with contact centers remains low.

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Can generative AI enable contact centers to deliver on their promise?

The network continues to grow in importance as a strategic business asset. A recent joint study between ZK Research and The Cube Research found that 93% of organizations felt the network was more critical to business operations than two years ago. At the same time, 80% of respondents believe the network has grown in complexity in that same time frame. The continuation of these two trends will lead to an untenable situation.

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Extreme Networks and Intel partner up for better generative AI

Accenture Plc Tuesday announced the launch of the Accenture AI Refinery framework, developed on Nvidia Corp.’s new AI Foundry service. The offering, designed to enable clients to build custom large language models using Llama 3.1 models, enables enterprises to refine and personalize these models with their own data and processes to create domain-specific generative AI solutions.

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Nvidia works with Accenture to pioneer custom Llama large language models

The artificial intelligence industry is filled with big vendors and upstarts, and Amazon Web Services Inc.’s AWS Summit in New York City earlier this months provided Amazon the platform to make its claim as the leader in AI. To do that, the company put Matt Wood (pictured), vice president of AI products at AWS, in the keynote spot.

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Five thoughts from Matt Wood’s keynote at AWS Summit New York

There has been plenty of hype and ballyhoo around artificial intelligence and networking, but much of the vendor focus has been AI for networking, where AI is used to improve network operations. The other side of the AI coin is networking for AI, where a network must be designed and provisioned to support an AI implementation. Though many businesses will likely deploy AI in the cloud, making the supporting network the problem of the hyperscaler, 58% of respondents to a recent ZK Research/theCube Research study stated they have deployed or will be deploying AI in their own private data center.

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Juniper Networks unveils Ops4AI Lab and designs to help customers fast-track AI deployments